会议信息

L&T 2027: International Learning and Technology Conference

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截稿日期:
2026-10-31 还有 17 天
通知日期:
会议日期:
2027-02-01
会议地点:
Jeddah, Saudi Arabia
届数:
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会伴指数 (CP-I)

54.1 / 100
全站第 954 名 / 共 5,696 个会议 · 前 17%
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
87
社区关注 (10%)
10
资料公开度 (15%)
55

用到的输入: 有据可查的届次：24 · 过去 24 个月打开过本页的研究者：3 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-14

征稿

L&T 2027 (International Learning and Technology Conference) is an academic conference held in Jeddah, Saudi Arabia on 2027-02-01. The paper submission deadline is 2026-10-31.

The 24th International Learning and Technology Conference (L&T 2027), themed “Architectures of the Future: Intelligent Technologies and Global Innovation," continues the legacy of one of Saudi Arabia's longest-standing academic technology conferences. Established in 2003, this interdisciplinary forum brings together researchers, educators, engineers, industry leaders, entrepreneurs, and policymakers to examine the technological foundations that will shape future economies and societies. The conference's objectives are to promote sustainable development by highlighting the integration of human-machine dynamics in education, enhance technological proficiency to prepare the next generation for future challenges and support Vision 2030 and the SDGs through aligned themes and discussions. We aim to foster innovation and collaboration between scholars, educators, and industry experts, and showcase best practices through case studies and successf​ul implementations of technology-driven educational strategies. By focusing on these objectives, the conference seeks to create a platform for knowledge exchange and to inspire transformative actions that contribute to a sustainable and prosperous future.​​​​​​ 1) AI Infrastructure, Advanced Computing and Intelligent Networks Topics include, but not limited to:​​ AI factories and next-generation data centers. High-performance computing and supercomputing. GPU, TPU, NPU, and AI accelerator architectures. Cloud-native AI and sovereign cloud platforms. Edge, fog, and distributed computing. Intelligent, autonomous, and software-defined networks. 5G, 6G, and future connectivity architectures. Data-center networking and high-speed interconnects. Resource scheduling and AI-workload orchestration. Energy-efficient computing architectures. Data-center cooling and thermal management. AI infrastructure monitoring, reliability, and resilience. Open computing architectures and interoperability. Quantum and neuromorphic computing. Computing infrastructure for foundation and multimodal models. 2) Artificial Intelligence, Foundation Models and Autonomous Systems Topics in this track could include -but not limited to-: Machine learning and deep learning. Generative AI and foundation models. Large language and multimodal models. Agentic AI and multi-agent systems. Autonomous decision-making systems. Robotics and intelligent automation. Human–robot and human–AI collaboration. Computer vision and spatial intelligence. Natural-language processing. Explainable and trustworthy AI. Federated and privacy-preserving learning. AI model optimization, compression, and efficient inference. Digital twins and intelligent simulation. Embodied and physical AI. AI evaluation, benchmarking, and assurance. ​​​​3) Energy, Sustainability and Resilient Engineering Systems Topics in this track could include -but not limited to-: Energy systems for AI infrastructure and data centers. Renewable energy integration. Smart grids and intelligent energy management. Energy storage and battery technologies. Green hydrogen and alternative energy systems. Energy-efficient AI and green computing. Carbon-aware computing and workload scheduling. Sustainable data-center design. Cooling technologies and water-resource management. AI for energy forecasting and optimization. Intelligent industrial and utility systems. Environmental monitoring and climate intelligence. Engineering solutions for climate resilience. Circular economy and sustainable technology lifecycles. Life-cycle assessment of digital infrastructure. ​​​4) Cybersecurity, Data Architecture, Governance and Digital Trust Topics in this track could include -but not limited to-: Cybersecurity for AI and critical digital infrastructure. Data architecture and engineering. Data governance, quality, and stewardship. Data sovereignty, residency, and cross-border data flows. Privacy-enhancing technologies. Secure cloud, edge, and distributed systems. AI security and adversarial machine learning. Security of foundation models and AI agents. Identity, authentication, and zero-trust architectures. Blockchain and distributed-ledger technologies. Digital identity and trust frameworks. Responsible AI and algorithmic accountability. AI governance, standards, and regulatory frameworks. Ethical use of data and intelligent technologies. Resilience, continuity, and disaster recovery. Digital infrastructure risk management. ​​​​​5) Intelligent Cities, Built Environments and Future Industries​ Topics in this track could include -but not limited to-: Smart and sustainable cities. Intelligent buildings and infrastructure. Urban digital twins. AI in architecture, engineering, and construction. Building information modelling and intelligent design. Smart mobility and autonomous transportation. Intelligent logistics and resilient supply chains. Industry 5.0 and smart manufacturing. Industrial AI, automation, and predictive maintenance. Intelligent healthcare systems. AI in energy, water, and public utilities. Precision agriculture and smart food systems. Aerospace, space, and satellite technologies. Smart ports and maritime systems. Human-centered and inclusive urban design. Climate-responsive built environments.​ 6) Intelligent Learning Ecosystems and Future Skills Topics in this track could include -but not limited to-: AI and generative AI in teaching and learning. Intelligent tutoring and adaptive learning systems. Learning analytics and predictive student support. AI agents in education. Immersive learning using VR, AR, and mixed reality. Digital twins of learning environments. Smart campuses and connected learning infrastructure. Digital transformation in higher education. AI governance, ethics, and academic integrity. Human-centered learning technologies. Inclusive, accessible, and assistive technologies. Future skills and workforce readiness. Lifelong learning and professional reskilling. Industry–academia collaboration in technology education. AI literacy and responsible technology education. Cybersecurity and privacy in educational environments. ​7) Semiconductors, Strategic Materials and Technology Supply Chains Topics in this track could include -but not limited to-: Semiconductor devices and fabrication technologies. AI chips and advanced processor technologies. Semiconductor packaging and chiplet architectures. Photonics and optical computing. Rare-earth elements and critical minerals. Advanced, smart, and functional materials. Nanotechnology and nanoscale devices. Materials for renewable-energy systems. Battery materials and energy storage. Materials for thermal management and data-center cooling. Advanced manufacturing and additive manufacturing. Sustainable sourcing and materials circularity. Semiconductor supply chains and technological sovereignty. Global technology supply-chain resilience. International standards and manufacturing collaboration. ​8) Innovation Ecosystems, Entrepreneurship and Global Collaboration Topics in this track could include -but not limited to-: National and regional AI innovation ecosystems. Digital entrepreneurship and technology startups. Commercialization of research and intellectual property. Venture capital and investment in emerging technologies. Public–private partnerships. University–industry–government collaboration. Global AI and digital-infrastructure partnerships. Technology transfer and innovation policy. Future business models and platform economies. Digital economy and emerging markets. Innovation clusters, special zones, and technology corridors. Talent mobility and international research collaboration. Women in technology, engineering, and innovation leadership. Inclusive innovation and technology for social impact. Responsible innovation and sustainable economic growth.
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